Ordinal Regression and Classification Algorithms
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Updated
Jan 29, 2021 - MATLAB
Ordinal Regression and Classification Algorithms
This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, and etc., which are simpler and easy to implement.
A system to recognize hand gestures by applying feature extraction, feature selection (PCA) and classification (SVM, decision tree, Neural Network) on the raw data captured by the sensors while performing the gestures.
Recognize traffic sign using Histogram of Oriented Gradients (HOG) and Colorspace based features. Support Vector Machines (SVM) is used for classifying images.
MATLAB Project to Classify Different Sleep Stages of the EEG Signals using Machine Learning (Random Forest and Support Vector Machine)
This repo created to detect Granuloma disorder that occurs on the tooth root. Program uses radiograph image as an input and will produce output based on features of radiograph image. Features are extracted using 2D Gabor Wavelet and classified using Support Vector Machine.
Solutions to Coursera Machine Learning course programming assignments
Voice Analyzer: Specialized in emotion detection, this Matlab app focuses on discerning anger and normal tones. Experience targeted insights, offering a nuanced perspective on voice sentiments.
Machine Learning Techniques to extract useful forecasts, conclusions and decision making in Quant Finance
Machine learning problem sets from Stanford University's Machine Learning course on Coursera
An Email Spam Filter. 📨
Machine learning techniques, such as Linear Regression, Logistic Regression, Neural Networks (feedforward propagation, backpropagation algorithms), Diagnosing Bias/Variance, Evaluating a Hypothesis, Learning Curves, Error Analysis, Support Vector Machines, K-Means Clustering, PCA, Anomaly Detection System, and Recommender System.
A Matlab implementation of support vector machines.
Evolutionary Support Vector Machine
A jigsaw puzzle solver term project.
Implementing gender recognition based on first 14 MFCC coefficients, pitch period, short time energy and spectral centroid
The project classifies characters (Hand-Written) by three algorithms Weighted kNN, Bayesian and SVM (using MATLAB R2016b and App Design GUI)
This is the recent work of my on the importance and application of mathematical function around its Hilbert function theory on artificial intelligence algorithms. The main motivation was the desire of improving the convergence rate and learning rate of various learning algorithms via Generalized Gaussian Radial Basis Function.
This repository contains codes for feature extraction and subsequent classification of surface electromyogram (EMG) signals.
Face Recognition using Support Vector Machine(SVM) on ORL Dataset
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